1. Technical Field
In one or more embodiments, a system and method for speech recognition is presented. More particularly, the one or more embodiments relate to a speech recognition learning system and method.
2. Background
A typical speech recognition system includes a single automatic speech recognition (ASR) engine to perform the recognition of an utterance. Speech Recognition systems generally rely on statistical principles to recognize speech accurately. Speech recognition events do not occur in a vacuum or in perfect scenarios. Recognition of speech can be influenced by numerous factors such as the environment in which the utterances was spoken and characteristics of a speaker's voice such as inflection or accent. Consequently, many ASR systems will not produce deterministic and equivalent results during a speech recognition event. For example, one ASR system may recognize one utterance better than another given a certain context. There are various examples of speech recognition implementations known in the art: U.S. Pat. Nos. 7,228,275, 6,526,380, 6,836,758, 6,671,669.
While the prior art system have been beneficial for their purposes, what is still needed is a speech recognition system that accounts for spoken utterances uttered in different contexts according to the environment in which it is spoken.